Overview

Dataset statistics

Number of variables29
Number of observations109
Missing cells100
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.8 KiB
Average record size in memory233.2 B

Variable types

Numeric9
Categorical20

Alerts

type has constant value "regular" Constant
airdate has constant value "2020-12-14" Constant
_embedded_show_dvdCountry has constant value "nan" Constant
url has a high cardinality: 109 distinct values High cardinality
name has a high cardinality: 96 distinct values High cardinality
_embedded_show_url has a high cardinality: 60 distinct values High cardinality
_embedded_show_name has a high cardinality: 60 distinct values High cardinality
_embedded_show_officialSite has a high cardinality: 56 distinct values High cardinality
_links_self_href has a high cardinality: 109 distinct values High cardinality
season is highly correlated with _embedded_show_updatedHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_updated is highly correlated with seasonHigh correlation
season is highly correlated with numberHigh correlation
number is highly correlated with seasonHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
name is highly correlated with type and 3 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_ended and 14 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
summary is highly correlated with type and 3 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 12 other fieldsHigh correlation
type is highly correlated with name and 16 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
airdate is highly correlated with name and 16 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_status is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
image is highly correlated with name and 16 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
_embedded_show_language is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with name and 16 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
id is highly correlated with airstamp and 14 other fieldsHigh correlation
name is highly correlated with season and 18 other fieldsHigh correlation
season is highly correlated with name and 12 other fieldsHigh correlation
number is highly correlated with name and 15 other fieldsHigh correlation
airtime is highly correlated with name and 16 other fieldsHigh correlation
airstamp is highly correlated with id and 20 other fieldsHigh correlation
runtime is highly correlated with name and 18 other fieldsHigh correlation
image is highly correlated with id and 22 other fieldsHigh correlation
summary is highly correlated with name and 3 other fieldsHigh correlation
_embedded_show_id is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_type is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_language is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_status is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with name and 19 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with name and 18 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_ended is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_weight is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 16 other fieldsHigh correlation
runtime has 5 (4.6%) missing values Missing
image has 74 (67.9%) missing values Missing
_embedded_show_runtime has 20 (18.3%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
image is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique

Reproduction

Analysis started2022-05-10 02:10:57.916266
Analysis finished2022-05-10 02:12:10.445778
Duration1 minute and 12.53 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019743.807
Minimum1945592
Maximum2318104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:10.563720image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1945592
5-th percentile1971207.4
Q11977834
median1985643
Q31991659
95-th percentile2243417.2
Maximum2318104
Range372512
Interquartile range (IQR)13825

Descriptive statistics

Standard deviation82477.3086
Coefficient of variation (CV)0.04083552988
Kurtosis3.555540579
Mean2019743.807
Median Absolute Deviation (MAD)7809
Skewness2.136445158
Sum220152075
Variance6802506434
MonotonicityNot monotonic
2022-05-09T21:12:10.877808image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19824031
 
0.9%
19776411
 
0.9%
19880541
 
0.9%
19880531
 
0.9%
19880521
 
0.9%
19878081
 
0.9%
19873251
 
0.9%
19873241
 
0.9%
19873231
 
0.9%
19872531
 
0.9%
Other values (99)99
90.8%
ValueCountFrequency (%)
19455921
0.9%
19679291
0.9%
19690621
0.9%
19707671
0.9%
19710561
0.9%
19712071
0.9%
19712081
0.9%
19712091
0.9%
19712101
0.9%
19712111
0.9%
ValueCountFrequency (%)
23181041
0.9%
22649421
0.9%
22649411
0.9%
22649401
0.9%
22649391
0.9%
22649381
0.9%
22111361
0.9%
21975951
0.9%
21972821
0.9%
21761311
0.9%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
https://www.tvmaze.com/episodes/1982403/volk-1x05-seria-05
 
1
https://www.tvmaze.com/episodes/1977641/to-love-1x30-episode-30
 
1
https://www.tvmaze.com/episodes/1988054/forever-love-1x03-episode-3
 
1
https://www.tvmaze.com/episodes/1988053/forever-love-1x02-episode-2
 
1
https://www.tvmaze.com/episodes/1988052/forever-love-1x01-episode-1
 
1
Other values (104)
104 

Length

Max length155
Median length91
Mean length76.75229358
Min length58

Characters and Unicode

Total characters8366
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1982403/volk-1x05-seria-05
2nd rowhttps://www.tvmaze.com/episodes/1982404/volk-1x06-seria-06
3rd rowhttps://www.tvmaze.com/episodes/2140387/going-seventeen-2020-12-14-going-vs-seventeen-1
4th rowhttps://www.tvmaze.com/episodes/1945592/my-little-invisible-being-1x12-episode-12
5th rowhttps://www.tvmaze.com/episodes/2065442/the-wonderland-of-ten-thousands-4x29-episode-29-157

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1982403/volk-1x05-seria-051
 
0.9%
https://www.tvmaze.com/episodes/1977641/to-love-1x30-episode-301
 
0.9%
https://www.tvmaze.com/episodes/1988054/forever-love-1x03-episode-31
 
0.9%
https://www.tvmaze.com/episodes/1988053/forever-love-1x02-episode-21
 
0.9%
https://www.tvmaze.com/episodes/1988052/forever-love-1x01-episode-11
 
0.9%
https://www.tvmaze.com/episodes/1987808/v-ritme-kolbasy-1x04-gibel-goliafa1
 
0.9%
https://www.tvmaze.com/episodes/1987325/beauty-and-the-boss-1x05-episode-51
 
0.9%
https://www.tvmaze.com/episodes/1987324/beauty-and-the-boss-1x04-episode-41
 
0.9%
https://www.tvmaze.com/episodes/1987323/beauty-and-the-boss-1x03-episode-31
 
0.9%
https://www.tvmaze.com/episodes/1987253/beauty-and-the-boss-1x02-episode-21
 
0.9%
Other values (99)99
90.8%

Length

2022-05-09T21:12:11.206295image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1982403/volk-1x05-seria-051
 
0.9%
https://www.tvmaze.com/episodes/1982428/vnutri-lapenko-3x02-2-seria1
 
0.9%
https://www.tvmaze.com/episodes/2140387/going-seventeen-2020-12-14-going-vs-seventeen-11
 
0.9%
https://www.tvmaze.com/episodes/1945592/my-little-invisible-being-1x12-episode-121
 
0.9%
https://www.tvmaze.com/episodes/2065442/the-wonderland-of-ten-thousands-4x29-episode-29-1571
 
0.9%
https://www.tvmaze.com/episodes/2071477/youths-in-the-breeze-1x07-the-boy-and-the-cat-071
 
0.9%
https://www.tvmaze.com/episodes/2071478/youths-in-the-breeze-1x08-the-boy-and-the-cat-081
 
0.9%
https://www.tvmaze.com/episodes/2080225/supreme-god-emperor-1x63-episode-631
 
0.9%
https://www.tvmaze.com/episodes/1977322/stjernestov-1x14-episode-141
 
0.9%
https://www.tvmaze.com/episodes/2003096/slepaa-10x100-cuzaa-igra1
 
0.9%
Other values (99)99
90.8%

Most occurring characters

ValueCountFrequency (%)
e734
 
8.8%
-634
 
7.6%
t565
 
6.8%
/545
 
6.5%
s514
 
6.1%
o411
 
4.9%
w352
 
4.2%
p317
 
3.8%
a302
 
3.6%
i299
 
3.6%
Other values (30)3693
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5584
66.7%
Decimal Number1276
 
15.3%
Other Punctuation872
 
10.4%
Dash Punctuation634
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e734
13.1%
t565
 
10.1%
s514
 
9.2%
o411
 
7.4%
w352
 
6.3%
p317
 
5.7%
a302
 
5.4%
i299
 
5.4%
m275
 
4.9%
h240
 
4.3%
Other values (16)1575
28.2%
Decimal Number
ValueCountFrequency (%)
1268
21.0%
2176
13.8%
0159
12.5%
9129
10.1%
7110
8.6%
8103
 
8.1%
493
 
7.3%
384
 
6.6%
579
 
6.2%
675
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/545
62.5%
.218
 
25.0%
:109
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-634
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5584
66.7%
Common2782
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e734
13.1%
t565
 
10.1%
s514
 
9.2%
o411
 
7.4%
w352
 
6.3%
p317
 
5.7%
a302
 
5.4%
i299
 
5.4%
m275
 
4.9%
h240
 
4.3%
Other values (16)1575
28.2%
Common
ValueCountFrequency (%)
-634
22.8%
/545
19.6%
1268
9.6%
.218
 
7.8%
2176
 
6.3%
0159
 
5.7%
9129
 
4.6%
7110
 
4.0%
:109
 
3.9%
8103
 
3.7%
Other values (4)331
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII8366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e734
 
8.8%
-634
 
7.6%
t565
 
6.8%
/545
 
6.5%
s514
 
6.1%
o411
 
4.9%
w352
 
4.2%
p317
 
3.8%
a302
 
3.6%
i299
 
3.6%
Other values (30)3693
44.1%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct96
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Episode 3
 
4
Episode 4
 
3
Episode 5
 
2
Episode 6
 
2
Episode 8
 
2
Other values (91)
96 

Length

Max length93
Median length62
Mean length17.4587156
Min length5

Characters and Unicode

Total characters1903
Distinct characters118
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)78.9%

Sample

1st rowСерия 05
2nd rowСерия 06
3rd rowGOING VS SEVENTEEN #1
4th rowEpisode 12
5th rowEpisode 29 (157)

Common Values

ValueCountFrequency (%)
Episode 34
 
3.7%
Episode 43
 
2.8%
Episode 52
 
1.8%
Episode 62
 
1.8%
Episode 82
 
1.8%
Episode 252
 
1.8%
Episode 22
 
1.8%
Episode 222
 
1.8%
Episode 12
 
1.8%
Episode 122
 
1.8%
Other values (86)86
78.9%

Length

2022-05-09T21:12:11.494966image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode39
 
10.8%
the23
 
6.4%
chapter13
 
3.6%
9
 
2.5%
36
 
1.7%
26
 
1.7%
16
 
1.7%
bölum5
 
1.4%
45
 
1.4%
144
 
1.1%
Other values (206)246
68.0%

Most occurring characters

ValueCountFrequency (%)
253
 
13.3%
e167
 
8.8%
o98
 
5.1%
i84
 
4.4%
s84
 
4.4%
a77
 
4.0%
r70
 
3.7%
t68
 
3.6%
p62
 
3.3%
d60
 
3.2%
Other values (108)880
46.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1140
59.9%
Uppercase Letter303
 
15.9%
Space Separator253
 
13.3%
Decimal Number140
 
7.4%
Other Punctuation53
 
2.8%
Dash Punctuation6
 
0.3%
Close Punctuation3
 
0.2%
Open Punctuation3
 
0.2%
Math Symbol2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e167
14.6%
o98
 
8.6%
i84
 
7.4%
s84
 
7.4%
a77
 
6.8%
r70
 
6.1%
t68
 
6.0%
p62
 
5.4%
d60
 
5.3%
h48
 
4.2%
Other values (42)322
28.2%
Uppercase Letter
ValueCountFrequency (%)
E50
16.5%
T33
 
10.9%
C32
 
10.6%
S16
 
5.3%
D15
 
5.0%
A12
 
4.0%
B12
 
4.0%
N12
 
4.0%
I10
 
3.3%
H9
 
3.0%
Other values (31)102
33.7%
Decimal Number
ValueCountFrequency (%)
232
22.9%
129
20.7%
016
11.4%
315
10.7%
413
9.3%
610
 
7.1%
58
 
5.7%
87
 
5.0%
77
 
5.0%
93
 
2.1%
Other Punctuation
ValueCountFrequency (%)
:18
34.0%
,10
18.9%
'8
15.1%
.7
 
13.2%
#6
 
11.3%
&2
 
3.8%
?1
 
1.9%
1
 
1.9%
Close Punctuation
ValueCountFrequency (%)
)2
66.7%
]1
33.3%
Open Punctuation
ValueCountFrequency (%)
(2
66.7%
[1
33.3%
Space Separator
ValueCountFrequency (%)
253
100.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1318
69.3%
Common460
 
24.2%
Cyrillic125
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e167
 
12.7%
o98
 
7.4%
i84
 
6.4%
s84
 
6.4%
a77
 
5.8%
r70
 
5.3%
t68
 
5.2%
p62
 
4.7%
d60
 
4.6%
E50
 
3.8%
Other values (41)498
37.8%
Cyrillic
ValueCountFrequency (%)
и11
 
8.8%
а9
 
7.2%
е9
 
7.2%
о8
 
6.4%
р7
 
5.6%
С6
 
4.8%
т5
 
4.0%
м5
 
4.0%
з4
 
3.2%
я4
 
3.2%
Other values (32)57
45.6%
Common
ValueCountFrequency (%)
253
55.0%
232
 
7.0%
129
 
6.3%
:18
 
3.9%
016
 
3.5%
315
 
3.3%
413
 
2.8%
,10
 
2.2%
610
 
2.2%
'8
 
1.7%
Other values (15)56
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1770
93.0%
Cyrillic125
 
6.6%
None7
 
0.4%
Punctuation1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
253
 
14.3%
e167
 
9.4%
o98
 
5.5%
i84
 
4.7%
s84
 
4.7%
a77
 
4.4%
r70
 
4.0%
t68
 
3.8%
p62
 
3.5%
d60
 
3.4%
Other values (62)747
42.2%
Cyrillic
ValueCountFrequency (%)
и11
 
8.8%
а9
 
7.2%
е9
 
7.2%
о8
 
6.4%
р7
 
5.6%
С6
 
4.8%
т5
 
4.0%
м5
 
4.0%
з4
 
3.2%
я4
 
3.2%
Other values (32)57
45.6%
None
ValueCountFrequency (%)
ö5
71.4%
å1
 
14.3%
é1
 
14.3%
Punctuation
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct14
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.2568807
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:11.791743image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile1224.4
Maximum2020
Range2019
Interquartile range (IQR)2

Descriptive statistics

Standard deviation462.1172772
Coefficient of variation (CV)4.044546588
Kurtosis13.90480014
Mean114.2568807
Median Absolute Deviation (MAD)0
Skewness3.9556711
Sum12454
Variance213552.3778
MonotonicityNot monotonic
2022-05-09T21:12:12.116768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
163
57.8%
216
 
14.7%
20206
 
5.5%
46
 
5.5%
33
 
2.8%
73
 
2.8%
63
 
2.8%
182
 
1.8%
122
 
1.8%
101
 
0.9%
Other values (4)4
 
3.7%
ValueCountFrequency (%)
163
57.8%
216
 
14.7%
33
 
2.8%
46
 
5.5%
63
 
2.8%
73
 
2.8%
91
 
0.9%
101
 
0.9%
122
 
1.8%
182
 
1.8%
ValueCountFrequency (%)
20206
5.5%
311
 
0.9%
301
 
0.9%
271
 
0.9%
182
 
1.8%
122
 
1.8%
101
 
0.9%
91
 
0.9%
73
2.8%
63
2.8%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct42
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.3853211
Minimum1
Maximum341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:12.367807image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q324
95-th percentile94
Maximum341
Range340
Interquartile range (IQR)20

Descriptive statistics

Standard deviation57.80201013
Coefficient of variation (CV)2.110693167
Kurtosis17.16520687
Mean27.3853211
Median Absolute Deviation (MAD)5
Skewness4.048931024
Sum2985
Variance3341.072375
MonotonicityNot monotonic
2022-05-09T21:12:12.710184image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
49
 
8.3%
38
 
7.3%
28
 
7.3%
17
 
6.4%
67
 
6.4%
87
 
6.4%
56
 
5.5%
75
 
4.6%
124
 
3.7%
104
 
3.7%
Other values (32)44
40.4%
ValueCountFrequency (%)
17
6.4%
28
7.3%
38
7.3%
49
8.3%
56
5.5%
67
6.4%
75
4.6%
87
6.4%
93
 
2.8%
104
3.7%
ValueCountFrequency (%)
3411
0.9%
3021
0.9%
3011
0.9%
2341
0.9%
1511
0.9%
1001
0.9%
851
0.9%
821
0.9%
651
0.9%
631
0.9%

type
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
regular
109 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters763
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular109
100.0%

Length

2022-05-09T21:12:13.213630image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:12:13.461451image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular109
100.0%

Most occurring characters

ValueCountFrequency (%)
r218
28.6%
e109
14.3%
g109
14.3%
u109
14.3%
l109
14.3%
a109
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter763
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r218
28.6%
e109
14.3%
g109
14.3%
u109
14.3%
l109
14.3%
a109
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin763
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r218
28.6%
e109
14.3%
g109
14.3%
u109
14.3%
l109
14.3%
a109
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII763
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r218
28.6%
e109
14.3%
g109
14.3%
u109
14.3%
l109
14.3%
a109
14.3%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2020-12-14
109 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1090
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-14
2nd row2020-12-14
3rd row2020-12-14
4th row2020-12-14
5th row2020-12-14

Common Values

ValueCountFrequency (%)
2020-12-14109
100.0%

Length

2022-05-09T21:12:13.642161image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:12:13.881165image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-14109
100.0%

Most occurring characters

ValueCountFrequency (%)
2327
30.0%
0218
20.0%
-218
20.0%
1218
20.0%
4109
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number872
80.0%
Dash Punctuation218
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2327
37.5%
0218
25.0%
1218
25.0%
4109
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1090
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2327
30.0%
0218
20.0%
-218
20.0%
1218
20.0%
4109
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2327
30.0%
0218
20.0%
-218
20.0%
1218
20.0%
4109
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1000.0 B
nan
74 
20:00
27 
12:00
 
1
06:00
 
1
17:35
 
1
Other values (5)
 
5

Length

Max length5
Median length3
Mean length3.642201835
Min length3

Characters and Unicode

Total characters397
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.3%

Sample

1st rownan
2nd rownan
3rd rownan
4th row12:00
5th rownan

Common Values

ValueCountFrequency (%)
nan74
67.9%
20:0027
 
24.8%
12:001
 
0.9%
06:001
 
0.9%
17:351
 
0.9%
00:001
 
0.9%
19:001
 
0.9%
20:151
 
0.9%
17:001
 
0.9%
21:001
 
0.9%

Length

2022-05-09T21:12:14.087897image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:12:14.448189image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan74
67.9%
20:0027
 
24.8%
12:001
 
0.9%
06:001
 
0.9%
17:351
 
0.9%
00:001
 
0.9%
19:001
 
0.9%
20:151
 
0.9%
17:001
 
0.9%
21:001
 
0.9%

Most occurring characters

ValueCountFrequency (%)
n148
37.3%
097
24.4%
a74
18.6%
:35
 
8.8%
230
 
7.6%
16
 
1.5%
72
 
0.5%
52
 
0.5%
61
 
0.3%
31
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter222
55.9%
Decimal Number140
35.3%
Other Punctuation35
 
8.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
097
69.3%
230
 
21.4%
16
 
4.3%
72
 
1.4%
52
 
1.4%
61
 
0.7%
31
 
0.7%
91
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
n148
66.7%
a74
33.3%
Other Punctuation
ValueCountFrequency (%)
:35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin222
55.9%
Common175
44.1%

Most frequent character per script

Common
ValueCountFrequency (%)
097
55.4%
:35
 
20.0%
230
 
17.1%
16
 
3.4%
72
 
1.1%
52
 
1.1%
61
 
0.6%
31
 
0.6%
91
 
0.6%
Latin
ValueCountFrequency (%)
n148
66.7%
a74
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n148
37.3%
097
24.4%
a74
18.6%
:35
 
8.8%
230
 
7.6%
16
 
1.5%
72
 
0.5%
52
 
0.5%
61
 
0.3%
31
 
0.3%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct17
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2020-12-14T12:00:00+00:00
78 
2020-12-14T17:00:00+00:00
 
5
2020-12-14T04:00:00+00:00
 
5
2020-12-14T09:00:00+00:00
 
5
2020-12-14T00:00:00+00:00
 
2
Other values (12)
14 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2725
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)9.2%

Sample

1st row2020-12-14T00:00:00+00:00
2nd row2020-12-14T00:00:00+00:00
3rd row2020-12-14T03:00:00+00:00
4th row2020-12-14T04:00:00+00:00
5th row2020-12-14T04:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-14T12:00:00+00:0078
71.6%
2020-12-14T17:00:00+00:005
 
4.6%
2020-12-14T04:00:00+00:005
 
4.6%
2020-12-14T09:00:00+00:005
 
4.6%
2020-12-14T00:00:00+00:002
 
1.8%
2020-12-14T11:00:00+00:002
 
1.8%
2020-12-14T19:00:00+00:002
 
1.8%
2020-12-15T01:00:00+00:001
 
0.9%
2020-12-14T22:00:00+00:001
 
0.9%
2020-12-14T19:15:00+00:001
 
0.9%
Other values (7)7
 
6.4%

Length

2022-05-09T21:12:14.703919image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-14t12:00:00+00:0078
71.6%
2020-12-14t04:00:00+00:005
 
4.6%
2020-12-14t09:00:00+00:005
 
4.6%
2020-12-14t17:00:00+00:005
 
4.6%
2020-12-14t00:00:00+00:002
 
1.8%
2020-12-14t11:00:00+00:002
 
1.8%
2020-12-14t19:00:00+00:002
 
1.8%
2020-12-14t15:00:00+00:001
 
0.9%
2020-12-14t05:00:00+00:001
 
0.9%
2020-12-14t05:35:00+00:001
 
0.9%
Other values (7)7
 
6.4%

Most occurring characters

ValueCountFrequency (%)
01105
40.6%
2408
 
15.0%
:327
 
12.0%
1313
 
11.5%
-218
 
8.0%
4113
 
4.1%
T109
 
4.0%
+109
 
4.0%
98
 
0.3%
57
 
0.3%
Other values (3)8
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1962
72.0%
Other Punctuation327
 
12.0%
Dash Punctuation218
 
8.0%
Uppercase Letter109
 
4.0%
Math Symbol109
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01105
56.3%
2408
 
20.8%
1313
 
16.0%
4113
 
5.8%
98
 
0.4%
57
 
0.4%
75
 
0.3%
32
 
0.1%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:327
100.0%
Dash Punctuation
ValueCountFrequency (%)
-218
100.0%
Uppercase Letter
ValueCountFrequency (%)
T109
100.0%
Math Symbol
ValueCountFrequency (%)
+109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2616
96.0%
Latin109
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01105
42.2%
2408
 
15.6%
:327
 
12.5%
1313
 
12.0%
-218
 
8.3%
4113
 
4.3%
+109
 
4.2%
98
 
0.3%
57
 
0.3%
75
 
0.2%
Other values (2)3
 
0.1%
Latin
ValueCountFrequency (%)
T109
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2725
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01105
40.6%
2408
 
15.0%
:327
 
12.0%
1313
 
11.5%
-218
 
8.0%
4113
 
4.1%
T109
 
4.0%
+109
 
4.0%
98
 
0.3%
57
 
0.3%
Other values (3)8
 
0.3%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)32.7%
Missing5
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean41.15384615
Minimum4
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:14.933090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q122.75
median45
Q355.25
95-th percentile88.35
Maximum180
Range176
Interquartile range (IQR)32.5

Descriptive statistics

Standard deviation28.47133433
Coefficient of variation (CV)0.6918268154
Kurtosis6.00127731
Mean41.15384615
Median Absolute Deviation (MAD)15
Skewness1.900854708
Sum4280
Variance810.6168783
MonotonicityNot monotonic
2022-05-09T21:12:15.252891image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
4516
14.7%
2312
 
11.0%
6012
 
11.0%
207
 
6.4%
304
 
3.7%
104
 
3.7%
584
 
3.7%
1203
 
2.8%
373
 
2.8%
483
 
2.8%
Other values (24)36
33.0%
(Missing)5
 
4.6%
ValueCountFrequency (%)
41
 
0.9%
52
 
1.8%
72
 
1.8%
104
3.7%
113
2.8%
122
 
1.8%
153
2.8%
181
 
0.9%
207
6.4%
221
 
0.9%
ValueCountFrequency (%)
1801
 
0.9%
1301
 
0.9%
1203
 
2.8%
901
 
0.9%
791
 
0.9%
6012
11.0%
584
 
3.7%
571
 
0.9%
562
 
1.8%
553
 
2.8%

image
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct35
Distinct (%)100.0%
Missing74
Missing (%)67.9%
Memory size1000.0 B
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726348.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726348.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722210.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722210.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722211.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722211.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722212.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722212.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722213.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722213.jpg'}
 
1
Other values (30)
30 

Length

Max length176
Median length176
Mean length176
Min length176

Characters and Unicode

Total characters6160
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726348.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726348.jpg'}
2nd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721853.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721853.jpg'}
3rd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/319/799925.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/319/799925.jpg'}
4th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722184.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722184.jpg'}
5th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722185.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722185.jpg'}

Common Values

ValueCountFrequency (%)
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726348.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726348.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722210.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722210.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722211.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722211.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722212.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722212.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722213.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722213.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722214.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722214.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722215.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722215.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722216.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722216.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722217.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722217.jpg'}1
 
0.9%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722218.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722218.jpg'}1
 
0.9%
Other values (25)25
 
22.9%
(Missing)74
67.9%

Length

2022-05-09T21:12:15.565794image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
medium35
25.0%
original35
25.0%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722184.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722187.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/722186.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722186.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/722185.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722185.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/722184.jpg1
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/319/799925.jpg1
 
0.7%
Other values (62)62
44.3%

Most occurring characters

ValueCountFrequency (%)
/490
 
8.0%
a420
 
6.8%
t385
 
6.2%
m350
 
5.7%
i350
 
5.7%
s315
 
5.1%
e280
 
4.5%
'280
 
4.5%
o245
 
4.0%
p245
 
4.0%
Other values (28)2800
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4130
67.0%
Other Punctuation1155
 
18.8%
Decimal Number630
 
10.2%
Space Separator105
 
1.7%
Connector Punctuation70
 
1.1%
Close Punctuation35
 
0.6%
Open Punctuation35
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a420
 
10.2%
t385
 
9.3%
m350
 
8.5%
i350
 
8.5%
s315
 
7.6%
e280
 
6.8%
o245
 
5.9%
p245
 
5.9%
g210
 
5.1%
c210
 
5.1%
Other values (9)1120
27.1%
Decimal Number
ValueCountFrequency (%)
2220
34.9%
8152
24.1%
784
 
13.3%
162
 
9.8%
928
 
4.4%
522
 
3.5%
320
 
3.2%
018
 
2.9%
412
 
1.9%
612
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/490
42.4%
'280
24.2%
.210
18.2%
:140
 
12.1%
,35
 
3.0%
Space Separator
ValueCountFrequency (%)
105
100.0%
Connector Punctuation
ValueCountFrequency (%)
_70
100.0%
Close Punctuation
ValueCountFrequency (%)
}35
100.0%
Open Punctuation
ValueCountFrequency (%)
{35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4130
67.0%
Common2030
33.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/490
24.1%
'280
13.8%
2220
10.8%
.210
10.3%
8152
 
7.5%
:140
 
6.9%
105
 
5.2%
784
 
4.1%
_70
 
3.4%
162
 
3.1%
Other values (9)217
10.7%
Latin
ValueCountFrequency (%)
a420
 
10.2%
t385
 
9.3%
m350
 
8.5%
i350
 
8.5%
s315
 
7.6%
e280
 
6.8%
o245
 
5.9%
p245
 
5.9%
g210
 
5.1%
c210
 
5.1%
Other values (9)1120
27.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII6160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/490
 
8.0%
a420
 
6.8%
t385
 
6.2%
m350
 
5.7%
i350
 
5.7%
s315
 
5.1%
e280
 
4.5%
'280
 
4.5%
o245
 
4.0%
p245
 
4.0%
Other values (28)2800
45.5%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct33
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size1000.0 B
nan
77 
<p>While Peter and Vincent fight for their lives in the Congo, Zora prepares everything in Dublin for a hostile takeover of the Swann Empire. Meanwhile, Peter's daughter Jane starts an affair with Vincent's younger brother Danny and gets on the wrong track. In the Congo, Grace is seriously ill with the Marburg virus and urgently needs medical help.</p>
 
1
<p>An old man wants to see his wife smile one more time before he takes his last breath.</p>
 
1
<p>Contestants are quizzed on their English and Botany knowledge as they race towards the second elimination point.  </p>
 
1
<p>Mr. Jan Sport and Mr. Barry-Thunderf*ck sit down with Mr. Royale to chat about how they met their queens, how their queens are making it through Covid, and some special talents of their own!</p>
 
1
Other values (28)
28 

Length

Max length354
Median length3
Mean length51.77981651
Min length3

Characters and Unicode

Total characters5644
Distinct characters62
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)29.4%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan77
70.6%
<p>While Peter and Vincent fight for their lives in the Congo, Zora prepares everything in Dublin for a hostile takeover of the Swann Empire. Meanwhile, Peter's daughter Jane starts an affair with Vincent's younger brother Danny and gets on the wrong track. In the Congo, Grace is seriously ill with the Marburg virus and urgently needs medical help.</p>1
 
0.9%
<p>An old man wants to see his wife smile one more time before he takes his last breath.</p>1
 
0.9%
<p>Contestants are quizzed on their English and Botany knowledge as they race towards the second elimination point.  </p>1
 
0.9%
<p>Mr. Jan Sport and Mr. Barry-Thunderf*ck sit down with Mr. Royale to chat about how they met their queens, how their queens are making it through Covid, and some special talents of their own!</p>1
 
0.9%
<p>Janejira's death has been concluded as a case of suicide. But a lot are still seeking justice for her. And the more you find the truth, the riskier it becomes. Yet this makes Tan and Bun's relationship even closer.</p>1
 
0.9%
<p>Everything reaches a turning point on the last night of "Ripper," as the dancers pull off a jaw-dropping finale and shocking secrets are revealed.</p>1
 
0.9%
<p>The dancers step up with a viral video to save the school from the expose's fallout. Armed with new evidence, Officer Cruz makes an arrest.</p><p><br /> </p>1
 
0.9%
<p>A photo shoot sheds new light on problems within the group. Neveah pays a price with Madame for talking to the press. Cassie's condition takes a turn.</p><p><br /> </p>1
 
0.9%
<p>Neveah, June and Bette's undercover sting to catch a predator goes sideways. Mixing business with pleasure puts Madame's reign at risk.</p><p><br /> </p>1
 
0.9%
Other values (23)23
 
21.1%

Length

2022-05-09T21:12:15.873534image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan77
 
7.9%
the37
 
3.8%
and36
 
3.7%
a35
 
3.6%
to29
 
3.0%
with16
 
1.6%
of15
 
1.5%
for12
 
1.2%
11
 
1.1%
p11
 
1.1%
Other values (510)693
71.3%

Most occurring characters

ValueCountFrequency (%)
853
15.1%
e487
 
8.6%
a439
 
7.8%
n439
 
7.8%
t341
 
6.0%
i286
 
5.1%
r281
 
5.0%
s280
 
5.0%
o276
 
4.9%
h188
 
3.3%
Other values (52)1774
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4251
75.3%
Space Separator864
 
15.3%
Math Symbol182
 
3.2%
Other Punctuation168
 
3.0%
Uppercase Letter164
 
2.9%
Dash Punctuation15
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e487
11.5%
a439
10.3%
n439
10.3%
t341
 
8.0%
i286
 
6.7%
r281
 
6.6%
s280
 
6.6%
o276
 
6.5%
h188
 
4.4%
l160
 
3.8%
Other values (16)1074
25.3%
Uppercase Letter
ValueCountFrequency (%)
T16
 
9.8%
A15
 
9.1%
B13
 
7.9%
H13
 
7.9%
M11
 
6.7%
C10
 
6.1%
S10
 
6.1%
D9
 
5.5%
R9
 
5.5%
J8
 
4.9%
Other values (12)50
30.5%
Other Punctuation
ValueCountFrequency (%)
.51
30.4%
/50
29.8%
,41
24.4%
'20
 
11.9%
!2
 
1.2%
"2
 
1.2%
*1
 
0.6%
:1
 
0.6%
Space Separator
ValueCountFrequency (%)
853
98.7%
 11
 
1.3%
Math Symbol
ValueCountFrequency (%)
>91
50.0%
<91
50.0%
Dash Punctuation
ValueCountFrequency (%)
-12
80.0%
3
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4415
78.2%
Common1229
 
21.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e487
 
11.0%
a439
 
9.9%
n439
 
9.9%
t341
 
7.7%
i286
 
6.5%
r281
 
6.4%
s280
 
6.3%
o276
 
6.3%
h188
 
4.3%
l160
 
3.6%
Other values (38)1238
28.0%
Common
ValueCountFrequency (%)
853
69.4%
>91
 
7.4%
<91
 
7.4%
.51
 
4.1%
/50
 
4.1%
,41
 
3.3%
'20
 
1.6%
-12
 
1.0%
 11
 
0.9%
3
 
0.2%
Other values (4)6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII5630
99.8%
None11
 
0.2%
Punctuation3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
853
15.2%
e487
 
8.7%
a439
 
7.8%
n439
 
7.8%
t341
 
6.1%
i286
 
5.1%
r281
 
5.0%
s280
 
5.0%
o276
 
4.9%
h188
 
3.3%
Other values (50)1760
31.3%
None
ValueCountFrequency (%)
 11
100.0%
Punctuation
ValueCountFrequency (%)
3
100.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct60
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42982.59633
Minimum802
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:16.211656image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum802
5-th percentile15250
Q135597
median49081
Q352524
95-th percentile59622
Maximum61755
Range60953
Interquartile range (IQR)16927

Descriptive statistics

Standard deviation14500.1953
Coefficient of variation (CV)0.3373503822
Kurtosis0.372657519
Mean42982.59633
Median Absolute Deviation (MAD)5788
Skewness-1.09985353
Sum4685103
Variance210255663.8
MonotonicityNot monotonic
2022-05-09T21:12:16.520312image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2591013
 
11.9%
4329310
 
9.2%
525248
 
7.3%
524795
 
4.6%
519545
 
4.6%
601565
 
4.6%
549963
 
2.8%
152502
 
1.8%
521592
 
1.8%
521082
 
1.8%
Other values (50)54
49.5%
ValueCountFrequency (%)
8021
0.9%
25041
0.9%
60901
0.9%
61461
0.9%
108211
0.9%
152502
1.8%
174471
0.9%
175841
0.9%
189711
0.9%
224731
0.9%
ValueCountFrequency (%)
617551
 
0.9%
601565
4.6%
588211
 
0.9%
584261
 
0.9%
583671
 
0.9%
570091
 
0.9%
568481
 
0.9%
566551
 
0.9%
550191
 
0.9%
549963
2.8%

_embedded_show_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct60
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
https://www.tvmaze.com/shows/25910/hilda
13 
https://www.tvmaze.com/shows/43293/tiny-pretty-things
10 
https://www.tvmaze.com/shows/52524/forever-love
https://www.tvmaze.com/shows/52479/beauty-and-the-boss
 
5
https://www.tvmaze.com/shows/51954/the-runner
 
5
Other values (55)
68 

Length

Max length67
Median length57
Mean length48.5412844
Min length39

Characters and Unicode

Total characters5291
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)42.2%

Sample

1st rowhttps://www.tvmaze.com/shows/52181/volk
2nd rowhttps://www.tvmaze.com/shows/52181/volk
3rd rowhttps://www.tvmaze.com/shows/56655/going-seventeen
4th rowhttps://www.tvmaze.com/shows/50916/my-little-invisible-being
5th rowhttps://www.tvmaze.com/shows/54610/the-wonderland-of-ten-thousands

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/25910/hilda13
 
11.9%
https://www.tvmaze.com/shows/43293/tiny-pretty-things10
 
9.2%
https://www.tvmaze.com/shows/52524/forever-love8
 
7.3%
https://www.tvmaze.com/shows/52479/beauty-and-the-boss5
 
4.6%
https://www.tvmaze.com/shows/51954/the-runner5
 
4.6%
https://www.tvmaze.com/shows/60156/efsane-t5
 
4.6%
https://www.tvmaze.com/shows/54996/the-silent-criminal3
 
2.8%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
1.8%
https://www.tvmaze.com/shows/52159/to-love2
 
1.8%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
1.8%
Other values (50)54
49.5%

Length

2022-05-09T21:12:16.897303image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/25910/hilda13
 
11.9%
https://www.tvmaze.com/shows/43293/tiny-pretty-things10
 
9.2%
https://www.tvmaze.com/shows/52524/forever-love8
 
7.3%
https://www.tvmaze.com/shows/52479/beauty-and-the-boss5
 
4.6%
https://www.tvmaze.com/shows/51954/the-runner5
 
4.6%
https://www.tvmaze.com/shows/60156/efsane-t5
 
4.6%
https://www.tvmaze.com/shows/54996/the-silent-criminal3
 
2.8%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
1.8%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
1.8%
https://www.tvmaze.com/shows/42412/professionals2
 
1.8%
Other values (50)54
49.5%

Most occurring characters

ValueCountFrequency (%)
/545
 
10.3%
t458
 
8.7%
w450
 
8.5%
s405
 
7.7%
o294
 
5.6%
h291
 
5.5%
e286
 
5.4%
m241
 
4.6%
.218
 
4.1%
a197
 
3.7%
Other values (30)1906
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3715
70.2%
Other Punctuation872
 
16.5%
Decimal Number545
 
10.3%
Dash Punctuation159
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t458
12.3%
w450
12.1%
s405
10.9%
o294
 
7.9%
h291
 
7.8%
e286
 
7.7%
m241
 
6.5%
a197
 
5.3%
v141
 
3.8%
p136
 
3.7%
Other values (16)816
22.0%
Decimal Number
ValueCountFrequency (%)
5106
19.4%
282
15.0%
470
12.8%
160
11.0%
955
10.1%
048
8.8%
640
 
7.3%
336
 
6.6%
724
 
4.4%
824
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/545
62.5%
.218
 
25.0%
:109
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3715
70.2%
Common1576
29.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t458
12.3%
w450
12.1%
s405
10.9%
o294
 
7.9%
h291
 
7.8%
e286
 
7.7%
m241
 
6.5%
a197
 
5.3%
v141
 
3.8%
p136
 
3.7%
Other values (16)816
22.0%
Common
ValueCountFrequency (%)
/545
34.6%
.218
 
13.8%
-159
 
10.1%
:109
 
6.9%
5106
 
6.7%
282
 
5.2%
470
 
4.4%
160
 
3.8%
955
 
3.5%
048
 
3.0%
Other values (4)124
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII5291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/545
 
10.3%
t458
 
8.7%
w450
 
8.5%
s405
 
7.7%
o294
 
5.6%
h291
 
5.5%
e286
 
5.4%
m241
 
4.6%
.218
 
4.1%
a197
 
3.7%
Other values (30)1906
36.0%

_embedded_show_name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct60
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Hilda
13 
Tiny Pretty Things
10 
Forever Love
Beauty and the Boss
 
5
The Runner
 
5
Other values (55)
68 

Length

Max length33
Median length22
Mean length13.66055046
Min length4

Characters and Unicode

Total characters1489
Distinct characters88
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)42.2%

Sample

1st rowВолк
2nd rowВолк
3rd rowGoing Seventeen
4th rowMy Little Invisible Being
5th rowThe Wonderland of Ten Thousands

Common Values

ValueCountFrequency (%)
Hilda13
 
11.9%
Tiny Pretty Things10
 
9.2%
Forever Love8
 
7.3%
Beauty and the Boss5
 
4.6%
The Runner5
 
4.6%
Efsane T5
 
4.6%
The Silent Criminal3
 
2.8%
The Young Turks2
 
1.8%
To Love2
 
1.8%
Psych Hunter2
 
1.8%
Other values (50)54
49.5%

Length

2022-05-09T21:12:17.247352image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the23
 
8.6%
hilda13
 
4.9%
love12
 
4.5%
pretty10
 
3.7%
things10
 
3.7%
tiny10
 
3.7%
forever8
 
3.0%
of6
 
2.2%
and6
 
2.2%
efsane5
 
1.9%
Other values (127)165
61.6%

Most occurring characters

ValueCountFrequency (%)
e161
 
10.8%
159
 
10.7%
n92
 
6.2%
i79
 
5.3%
r78
 
5.2%
a74
 
5.0%
t70
 
4.7%
o66
 
4.4%
s64
 
4.3%
h55
 
3.7%
Other values (78)591
39.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1079
72.5%
Uppercase Letter239
 
16.1%
Space Separator159
 
10.7%
Other Punctuation7
 
0.5%
Decimal Number5
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e161
14.9%
n92
 
8.5%
i79
 
7.3%
r78
 
7.2%
a74
 
6.9%
t70
 
6.5%
o66
 
6.1%
s64
 
5.9%
h55
 
5.1%
l43
 
4.0%
Other values (40)297
27.5%
Uppercase Letter
ValueCountFrequency (%)
T55
23.0%
B21
 
8.8%
P18
 
7.5%
H17
 
7.1%
L14
 
5.9%
F13
 
5.4%
M12
 
5.0%
S12
 
5.0%
R10
 
4.2%
C10
 
4.2%
Other values (20)57
23.8%
Other Punctuation
ValueCountFrequency (%)
.2
28.6%
'2
28.6%
!2
28.6%
,1
14.3%
Decimal Number
ValueCountFrequency (%)
03
60.0%
21
 
20.0%
31
 
20.0%
Space Separator
ValueCountFrequency (%)
159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1241
83.3%
Common171
 
11.5%
Cyrillic77
 
5.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e161
 
13.0%
n92
 
7.4%
i79
 
6.4%
r78
 
6.3%
a74
 
6.0%
t70
 
5.6%
o66
 
5.3%
s64
 
5.2%
h55
 
4.4%
T55
 
4.4%
Other values (40)447
36.0%
Cyrillic
ValueCountFrequency (%)
о9
 
11.7%
л6
 
7.8%
т6
 
7.8%
р6
 
7.8%
а5
 
6.5%
к5
 
6.5%
е5
 
6.5%
В4
 
5.2%
н3
 
3.9%
у3
 
3.9%
Other values (20)25
32.5%
Common
ValueCountFrequency (%)
159
93.0%
03
 
1.8%
.2
 
1.2%
'2
 
1.2%
!2
 
1.2%
21
 
0.6%
31
 
0.6%
,1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1409
94.6%
Cyrillic77
 
5.2%
None3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e161
 
11.4%
159
 
11.3%
n92
 
6.5%
i79
 
5.6%
r78
 
5.5%
a74
 
5.3%
t70
 
5.0%
o66
 
4.7%
s64
 
4.5%
h55
 
3.9%
Other values (45)511
36.3%
Cyrillic
ValueCountFrequency (%)
о9
 
11.7%
л6
 
7.8%
т6
 
7.8%
р6
 
7.8%
а5
 
6.5%
к5
 
6.5%
е5
 
6.5%
В4
 
5.2%
н3
 
3.9%
у3
 
3.9%
Other values (20)25
32.5%
None
ValueCountFrequency (%)
Ç1
33.3%
ø1
33.3%
ä1
33.3%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Scripted
58 
Animation
19 
Talk Show
Documentary
Reality
Other values (4)

Length

Max length11
Median length8
Mean length8.28440367
Min length4

Characters and Unicode

Total characters903
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowScripted
2nd rowScripted
3rd rowVariety
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted58
53.2%
Animation19
 
17.4%
Talk Show9
 
8.3%
Documentary8
 
7.3%
Reality7
 
6.4%
News3
 
2.8%
Variety2
 
1.8%
Game Show2
 
1.8%
Sports1
 
0.9%

Length

2022-05-09T21:12:17.544837image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:12:17.955751image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted58
48.3%
animation19
 
15.8%
show11
 
9.2%
talk9
 
7.5%
documentary8
 
6.7%
reality7
 
5.8%
news3
 
2.5%
variety2
 
1.7%
game2
 
1.7%
sports1
 
0.8%

Most occurring characters

ValueCountFrequency (%)
i105
11.6%
t95
10.5%
e80
 
8.9%
S70
 
7.8%
r69
 
7.6%
c66
 
7.3%
p59
 
6.5%
d58
 
6.4%
a47
 
5.2%
n46
 
5.1%
Other values (17)208
23.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter772
85.5%
Uppercase Letter120
 
13.3%
Space Separator11
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i105
13.6%
t95
12.3%
e80
10.4%
r69
8.9%
c66
8.5%
p59
7.6%
d58
7.5%
a47
6.1%
n46
6.0%
o39
 
5.1%
Other values (8)108
14.0%
Uppercase Letter
ValueCountFrequency (%)
S70
58.3%
A19
 
15.8%
T9
 
7.5%
D8
 
6.7%
R7
 
5.8%
N3
 
2.5%
V2
 
1.7%
G2
 
1.7%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin892
98.8%
Common11
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i105
11.8%
t95
10.7%
e80
9.0%
S70
 
7.8%
r69
 
7.7%
c66
 
7.4%
p59
 
6.6%
d58
 
6.5%
a47
 
5.3%
n46
 
5.2%
Other values (16)197
22.1%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII903
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i105
11.6%
t95
10.5%
e80
 
8.9%
S70
 
7.8%
r69
 
7.6%
c66
 
7.3%
p59
 
6.5%
d58
 
6.4%
a47
 
5.2%
n46
 
5.1%
Other values (17)208
23.0%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size1000.0 B
English
44 
Chinese
32 
Russian
Turkish
Norwegian
 
4
Other values (11)
15 

Length

Max length10
Median length7
Mean length6.972477064
Min length3

Characters and Unicode

Total characters760
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)6.4%

Sample

1st rowRussian
2nd rowRussian
3rd rowKorean
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
English44
40.4%
Chinese32
29.4%
Russian8
 
7.3%
Turkish6
 
5.5%
Norwegian4
 
3.7%
Korean2
 
1.8%
Swedish2
 
1.8%
Thai2
 
1.8%
Arabic2
 
1.8%
Spanish1
 
0.9%
Other values (6)6
 
5.5%

Length

2022-05-09T21:12:18.324225image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english44
40.4%
chinese32
29.4%
russian8
 
7.3%
turkish6
 
5.5%
norwegian4
 
3.7%
korean2
 
1.8%
swedish2
 
1.8%
thai2
 
1.8%
arabic2
 
1.8%
spanish1
 
0.9%
Other values (6)6
 
5.5%

Most occurring characters

ValueCountFrequency (%)
i104
13.7%
s102
13.4%
n97
12.8%
h89
11.7%
e75
9.9%
g49
6.4%
E44
5.8%
l44
5.8%
C32
 
4.2%
a25
 
3.3%
Other values (22)99
13.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter652
85.8%
Uppercase Letter108
 
14.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i104
16.0%
s102
15.6%
n97
14.9%
h89
13.7%
e75
11.5%
g49
7.5%
l44
6.7%
a25
 
3.8%
u18
 
2.8%
r16
 
2.5%
Other values (10)33
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
E44
40.7%
C32
29.6%
R8
 
7.4%
T8
 
7.4%
N4
 
3.7%
S3
 
2.8%
A2
 
1.9%
L2
 
1.9%
K2
 
1.9%
P1
 
0.9%
Other values (2)2
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin760
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i104
13.7%
s102
13.4%
n97
12.8%
h89
11.7%
e75
9.9%
g49
6.4%
E44
5.8%
l44
5.8%
C32
 
4.2%
a25
 
3.3%
Other values (22)99
13.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i104
13.7%
s102
13.4%
n97
12.8%
h89
11.7%
e75
9.9%
g49
6.4%
E44
5.8%
l44
5.8%
C32
 
4.2%
a25
 
3.3%
Other values (22)99
13.0%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct26
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
[]
30 
['Drama', 'Romance']
17 
['Adventure', 'Children', 'Fantasy']
13 
['Drama', 'Romance', 'Mystery']
10 
['Drama']
Other values (21)
33 

Length

Max length36
Median length32
Mean length18.06422018
Min length2

Characters and Unicode

Total characters1969
Distinct characters31
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)11.9%

Sample

1st row['Drama', 'Adventure', 'Mystery']
2nd row['Drama', 'Adventure', 'Mystery']
3rd row[]
4th row['Comedy', 'Anime']
5th row['Anime', 'Fantasy', 'Romance']

Common Values

ValueCountFrequency (%)
[]30
27.5%
['Drama', 'Romance']17
15.6%
['Adventure', 'Children', 'Fantasy']13
11.9%
['Drama', 'Romance', 'Mystery']10
 
9.2%
['Drama']6
 
5.5%
['Comedy']6
 
5.5%
['Drama', 'Adventure', 'Mystery']2
 
1.8%
['Crime', 'Thriller', 'Mystery']2
 
1.8%
['Drama', 'Thriller', 'Mystery']2
 
1.8%
['Drama', 'Romance', 'History']2
 
1.8%
Other values (16)19
17.4%

Length

2022-05-09T21:12:18.623220image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama49
23.2%
romance32
15.2%
30
14.2%
adventure16
 
7.6%
fantasy16
 
7.6%
mystery16
 
7.6%
children15
 
7.1%
comedy11
 
5.2%
thriller7
 
3.3%
crime5
 
2.4%
Other values (6)14
 
6.6%

Most occurring characters

ValueCountFrequency (%)
'362
18.4%
a164
 
8.3%
e121
 
6.1%
r118
 
6.0%
[109
 
5.5%
]109
 
5.5%
m102
 
5.2%
,102
 
5.2%
102
 
5.2%
n87
 
4.4%
Other values (21)593
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1004
51.0%
Other Punctuation464
23.6%
Uppercase Letter181
 
9.2%
Open Punctuation109
 
5.5%
Close Punctuation109
 
5.5%
Space Separator102
 
5.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a164
16.3%
e121
12.1%
r118
11.8%
m102
10.2%
n87
8.7%
y63
 
6.3%
t56
 
5.6%
o53
 
5.3%
d43
 
4.3%
i39
 
3.9%
Other values (7)158
15.7%
Uppercase Letter
ValueCountFrequency (%)
D49
27.1%
R32
17.7%
C31
17.1%
A24
13.3%
F19
 
10.5%
M16
 
8.8%
T7
 
3.9%
H2
 
1.1%
S1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
'362
78.0%
,102
 
22.0%
Open Punctuation
ValueCountFrequency (%)
[109
100.0%
Close Punctuation
ValueCountFrequency (%)
]109
100.0%
Space Separator
ValueCountFrequency (%)
102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1185
60.2%
Common784
39.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a164
13.8%
e121
 
10.2%
r118
 
10.0%
m102
 
8.6%
n87
 
7.3%
y63
 
5.3%
t56
 
4.7%
o53
 
4.5%
D49
 
4.1%
d43
 
3.6%
Other values (16)329
27.8%
Common
ValueCountFrequency (%)
'362
46.2%
[109
 
13.9%
]109
 
13.9%
,102
 
13.0%
102
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1969
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'362
18.4%
a164
 
8.3%
e121
 
6.1%
r118
 
6.0%
[109
 
5.5%
]109
 
5.5%
m102
 
5.2%
,102
 
5.2%
102
 
5.2%
n87
 
4.4%
Other values (21)593
30.1%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Ended
55 
Running
34 
To Be Determined
20 

Length

Max length16
Median length5
Mean length7.642201835
Min length5

Characters and Unicode

Total characters833
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowEnded
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended55
50.5%
Running34
31.2%
To Be Determined20
 
18.3%

Length

2022-05-09T21:12:19.081428image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:12:19.322011image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
ended55
36.9%
running34
22.8%
to20
 
13.4%
be20
 
13.4%
determined20
 
13.4%

Most occurring characters

ValueCountFrequency (%)
n177
21.2%
e135
16.2%
d130
15.6%
E55
 
6.6%
i54
 
6.5%
40
 
4.8%
R34
 
4.1%
u34
 
4.1%
g34
 
4.1%
T20
 
2.4%
Other values (6)120
14.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter644
77.3%
Uppercase Letter149
 
17.9%
Space Separator40
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n177
27.5%
e135
21.0%
d130
20.2%
i54
 
8.4%
u34
 
5.3%
g34
 
5.3%
o20
 
3.1%
t20
 
3.1%
r20
 
3.1%
m20
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
E55
36.9%
R34
22.8%
T20
 
13.4%
B20
 
13.4%
D20
 
13.4%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin793
95.2%
Common40
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n177
22.3%
e135
17.0%
d130
16.4%
E55
 
6.9%
i54
 
6.8%
R34
 
4.3%
u34
 
4.3%
g34
 
4.3%
T20
 
2.5%
o20
 
2.5%
Other values (5)100
12.6%
Common
ValueCountFrequency (%)
40
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n177
21.2%
e135
16.2%
d130
15.6%
E55
 
6.6%
i54
 
6.5%
40
 
4.8%
R34
 
4.1%
u34
 
4.1%
g34
 
4.1%
T20
 
2.4%
Other values (6)120
14.4%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)28.1%
Missing20
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean40.26966292
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:19.542196image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10
Q122
median37
Q351
95-th percentile108
Maximum180
Range175
Interquartile range (IQR)29

Descriptive statistics

Standard deviation29.57761901
Coefficient of variation (CV)0.734488865
Kurtosis6.285256028
Mean40.26966292
Median Absolute Deviation (MAD)14
Skewness2.094527984
Sum3584
Variance874.8355465
MonotonicityNot monotonic
2022-05-09T21:12:19.791552image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
4515
13.8%
6014
12.8%
2413
11.9%
207
 
6.4%
105
 
4.6%
305
 
4.6%
153
 
2.8%
373
 
2.8%
1203
 
2.8%
482
 
1.8%
Other values (15)19
17.4%
(Missing)20
18.3%
ValueCountFrequency (%)
52
 
1.8%
72
 
1.8%
105
4.6%
111
 
0.9%
121
 
0.9%
153
2.8%
161
 
0.9%
207
6.4%
221
 
0.9%
231
 
0.9%
ValueCountFrequency (%)
1801
 
0.9%
1301
 
0.9%
1203
 
2.8%
901
 
0.9%
6014
12.8%
551
 
0.9%
512
 
1.8%
501
 
0.9%
482
 
1.8%
4515
13.8%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct30
Distinct (%)27.8%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean40.41666667
Minimum4
Maximum181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:20.007047image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.35
Q123
median40
Q357
95-th percentile79.5
Maximum181
Range177
Interquartile range (IQR)34

Descriptive statistics

Standard deviation28.10265727
Coefficient of variation (CV)0.6953234789
Kurtosis6.488265514
Mean40.41666667
Median Absolute Deviation (MAD)17
Skewness1.967172126
Sum4365
Variance789.7593458
MonotonicityNot monotonic
2022-05-09T21:12:20.238167image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4515
13.8%
2413
11.9%
6012
 
11.0%
5710
 
9.2%
207
 
6.4%
255
 
4.6%
504
 
3.7%
104
 
3.7%
303
 
2.8%
373
 
2.8%
Other values (20)32
29.4%
ValueCountFrequency (%)
41
 
0.9%
52
1.8%
72
1.8%
91
 
0.9%
104
3.7%
113
2.8%
122
1.8%
141
 
0.9%
153
2.8%
161
 
0.9%
ValueCountFrequency (%)
1811
 
0.9%
1301
 
0.9%
1203
 
2.8%
901
 
0.9%
6012
11.0%
582
 
1.8%
5710
9.2%
531
 
0.9%
504
 
3.7%
482
 
1.8%

_embedded_show_premiered
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct46
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2020-12-14
30 
2018-09-21
13 
2020-11-23
2020-11-16
2020-11-09
 
4
Other values (41)
49 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1090
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)33.0%

Sample

1st row2020-12-07
2nd row2020-12-07
3rd row2017-06-12
4th row2020-10-05
5th row2018-03-30

Common Values

ValueCountFrequency (%)
2020-12-1430
27.5%
2018-09-2113
 
11.9%
2020-11-238
 
7.3%
2020-11-165
 
4.6%
2020-11-094
 
3.7%
2020-12-074
 
3.7%
2020-11-303
 
2.8%
2013-12-242
 
1.8%
2020-11-192
 
1.8%
2020-12-132
 
1.8%
Other values (36)36
33.0%

Length

2022-05-09T21:12:20.512039image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1430
27.5%
2018-09-2113
 
11.9%
2020-11-238
 
7.3%
2020-11-165
 
4.6%
2020-11-094
 
3.7%
2020-12-074
 
3.7%
2020-11-303
 
2.8%
2020-12-132
 
1.8%
2020-11-192
 
1.8%
2013-12-242
 
1.8%
Other values (36)36
33.0%

Most occurring characters

ValueCountFrequency (%)
0249
22.8%
2248
22.8%
-218
20.0%
1214
19.6%
440
 
3.7%
936
 
3.3%
326
 
2.4%
824
 
2.2%
715
 
1.4%
611
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number872
80.0%
Dash Punctuation218
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0249
28.6%
2248
28.4%
1214
24.5%
440
 
4.6%
936
 
4.1%
326
 
3.0%
824
 
2.8%
715
 
1.7%
611
 
1.3%
59
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
-218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1090
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0249
22.8%
2248
22.8%
-218
20.0%
1214
19.6%
440
 
3.7%
936
 
3.3%
326
 
2.4%
824
 
2.2%
715
 
1.4%
611
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0249
22.8%
2248
22.8%
-218
20.0%
1214
19.6%
440
 
3.7%
936
 
3.3%
326
 
2.4%
824
 
2.2%
715
 
1.4%
611
 
1.0%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct15
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size1000.0 B
nan
54 
2020-12-14
23 
2021-01-05
2021-01-18
2020-12-28
 
3
Other values (10)
14 

Length

Max length10
Median length10
Mean length6.532110092
Min length3

Characters and Unicode

Total characters712
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.5%

Sample

1st row2020-12-28
2nd row2020-12-28
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan54
49.5%
2020-12-1423
21.1%
2021-01-058
 
7.3%
2021-01-187
 
6.4%
2020-12-283
 
2.8%
2020-12-222
 
1.8%
2020-12-302
 
1.8%
2020-12-162
 
1.8%
2020-12-232
 
1.8%
2020-12-241
 
0.9%
Other values (5)5
 
4.6%

Length

2022-05-09T21:12:20.739805image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan54
49.5%
2020-12-1423
21.1%
2021-01-058
 
7.3%
2021-01-187
 
6.4%
2020-12-283
 
2.8%
2020-12-222
 
1.8%
2020-12-302
 
1.8%
2020-12-162
 
1.8%
2020-12-232
 
1.8%
2020-12-241
 
0.9%
Other values (5)5
 
4.6%

Most occurring characters

ValueCountFrequency (%)
2162
22.8%
0120
16.9%
-110
15.4%
n108
15.2%
1106
14.9%
a54
 
7.6%
424
 
3.4%
812
 
1.7%
58
 
1.1%
34
 
0.6%
Other values (2)4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number440
61.8%
Lowercase Letter162
 
22.8%
Dash Punctuation110
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2162
36.8%
0120
27.3%
1106
24.1%
424
 
5.5%
812
 
2.7%
58
 
1.8%
34
 
0.9%
63
 
0.7%
71
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
n108
66.7%
a54
33.3%
Dash Punctuation
ValueCountFrequency (%)
-110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common550
77.2%
Latin162
 
22.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2162
29.5%
0120
21.8%
-110
20.0%
1106
19.3%
424
 
4.4%
812
 
2.2%
58
 
1.5%
34
 
0.7%
63
 
0.5%
71
 
0.2%
Latin
ValueCountFrequency (%)
n108
66.7%
a54
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2162
22.8%
0120
16.9%
-110
15.4%
n108
15.2%
1106
14.9%
a54
 
7.6%
424
 
3.4%
812
 
1.7%
58
 
1.1%
34
 
0.6%
Other values (2)4
 
0.6%

_embedded_show_officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct56
Distinct (%)51.4%
Missing0
Missing (%)0.0%
Memory size1000.0 B
nan
13 
https://www.netflix.com/title/80115346
13 
https://www.netflix.com/title/81017308
10 
https://v.qq.com/detail/m/mzc00200dnvb1wh.html
https://programme.mytvsuper.com/tc/130336/
 
5
Other values (51)
60 

Length

Max length105
Median length86
Mean length41.96330275
Min length3

Characters and Unicode

Total characters4574
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)39.4%

Sample

1st rowhttps://premier.one/show/12339
2nd rowhttps://premier.one/show/12339
3rd rownan
4th rowhttps://www.bilibili.com/bangumi/media/md28229943/
5th rowhttps://v.qq.com/detail/5/5cuf8ahvxvm2587.html

Common Values

ValueCountFrequency (%)
nan13
 
11.9%
https://www.netflix.com/title/8011534613
 
11.9%
https://www.netflix.com/title/8101730810
 
9.2%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html8
 
7.3%
https://programme.mytvsuper.com/tc/130336/5
 
4.6%
https://www.iqiyi.com/a_je0t80m6td.html3
 
2.8%
https://premier.one/show/123392
 
1.8%
https://www.tytnetwork.com2
 
1.8%
https://www.iqiyi.com/a_19rrhskr95.html2
 
1.8%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
1.8%
Other values (46)49
45.0%

Length

2022-05-09T21:12:21.043416image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan13
 
11.9%
https://www.netflix.com/title/8011534613
 
11.9%
https://www.netflix.com/title/8101730810
 
9.2%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html8
 
7.3%
https://programme.mytvsuper.com/tc/1303365
 
4.6%
https://www.iqiyi.com/a_je0t80m6td.html3
 
2.8%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
1.8%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
1.8%
https://viaplay.no/serier/professionals2
 
1.8%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
1.8%
Other values (46)49
45.0%

Most occurring characters

ValueCountFrequency (%)
/405
 
8.9%
t398
 
8.7%
e234
 
5.1%
s208
 
4.5%
.200
 
4.4%
w199
 
4.4%
h180
 
3.9%
o177
 
3.9%
m163
 
3.6%
i146
 
3.2%
Other values (64)2264
49.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2967
64.9%
Other Punctuation781
 
17.1%
Decimal Number569
 
12.4%
Uppercase Letter164
 
3.6%
Dash Punctuation51
 
1.1%
Math Symbol25
 
0.5%
Connector Punctuation17
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t398
13.4%
e234
 
7.9%
s208
 
7.0%
w199
 
6.7%
h180
 
6.1%
o177
 
6.0%
m163
 
5.5%
i146
 
4.9%
p145
 
4.9%
a131
 
4.4%
Other values (16)986
33.2%
Uppercase Letter
ValueCountFrequency (%)
E21
12.8%
B14
 
8.5%
A13
 
7.9%
D12
 
7.3%
P12
 
7.3%
M10
 
6.1%
C10
 
6.1%
U9
 
5.5%
T7
 
4.3%
Z7
 
4.3%
Other values (15)49
29.9%
Decimal Number
ValueCountFrequency (%)
0112
19.7%
197
17.0%
370
12.3%
862
10.9%
450
8.8%
541
 
7.2%
639
 
6.9%
238
 
6.7%
932
 
5.6%
728
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/405
51.9%
.200
25.6%
:96
 
12.3%
%57
 
7.3%
?11
 
1.4%
&8
 
1.0%
,2
 
0.3%
!1
 
0.1%
#1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=23
92.0%
+2
 
8.0%
Dash Punctuation
ValueCountFrequency (%)
-51
100.0%
Connector Punctuation
ValueCountFrequency (%)
_17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3131
68.5%
Common1443
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t398
 
12.7%
e234
 
7.5%
s208
 
6.6%
w199
 
6.4%
h180
 
5.7%
o177
 
5.7%
m163
 
5.2%
i146
 
4.7%
p145
 
4.6%
a131
 
4.2%
Other values (41)1150
36.7%
Common
ValueCountFrequency (%)
/405
28.1%
.200
13.9%
0112
 
7.8%
197
 
6.7%
:96
 
6.7%
370
 
4.9%
862
 
4.3%
%57
 
4.0%
-51
 
3.5%
450
 
3.5%
Other values (13)243
16.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII4574
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/405
 
8.9%
t398
 
8.7%
e234
 
5.1%
s208
 
4.5%
.200
 
4.4%
w199
 
4.4%
h180
 
3.9%
o177
 
3.9%
m163
 
3.6%
i146
 
3.2%
Other values (64)2264
49.5%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION

Distinct40
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.20183486
Minimum1
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:21.366365image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.4
Q115
median28
Q352
95-th percentile83
Maximum97
Range96
Interquartile range (IQR)37

Descriptive statistics

Standard deviation27.93702568
Coefficient of variation (CV)0.7717019259
Kurtosis-0.7407926463
Mean36.20183486
Median Absolute Deviation (MAD)16
Skewness0.7190510053
Sum3946
Variance780.477404
MonotonicityNot monotonic
2022-05-09T21:12:21.673954image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
8314
 
12.8%
3010
 
9.2%
5210
 
9.2%
138
 
7.3%
156
 
5.5%
16
 
5.5%
185
 
4.6%
254
 
3.7%
63
 
2.8%
283
 
2.8%
Other values (30)40
36.7%
ValueCountFrequency (%)
16
5.5%
21
 
0.9%
32
 
1.8%
42
 
1.8%
63
 
2.8%
81
 
0.9%
101
 
0.9%
112
 
1.8%
138
7.3%
141
 
0.9%
ValueCountFrequency (%)
972
 
1.8%
941
 
0.9%
871
 
0.9%
8314
12.8%
771
 
0.9%
751
 
0.9%
721
 
0.9%
651
 
0.9%
641
 
0.9%
631
 
0.9%

_embedded_show_dvdCountry
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
nan
109 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters327
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan109
100.0%

Length

2022-05-09T21:12:21.946019image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:12:22.178004image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan109
100.0%

Most occurring characters

ValueCountFrequency (%)
n218
66.7%
a109
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter327
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n218
66.7%
a109
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin327
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n218
66.7%
a109
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n218
66.7%
a109
33.3%

_embedded_show_summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct49
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
nan
23 
<p><b>Hilda</b> follows the adventures of a fearless blue-haired girl as she travels from her home in a vast magical wilderness full of elves and giants, to the bustling city of Trolberg, where she meets new friends and mysterious creatures who are stranger - and more dangerous - than she ever expected.</p>
13 
<p><b>Tiny Pretty Things</b> is set in the world of an elite ballet academy and charts the rise and fall of young adults who live far from their homes, each standing on the verge of greatness or ruin. As Chicago's only elite dance school, the Archer School of Ballet serves as the company school for the city's renowned professional company: City Works Ballet. The Archer School is an oasis for an array of dancers: rich and poor, from north and south, and a range of backgrounds. Yet they all share a rare talent and passion for dance, a loyal sense of community... and when it comes to their dreams, no Plan B.</p>
10 
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>
<p>A documentary series about Tofaş owners and culture from 7 regions of Turkey.</p>
 
5
Other values (44)
50 

Length

Max length913
Median length802
Mean length288.2844037
Min length3

Characters and Unicode

Total characters31423
Distinct characters121
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)34.9%

Sample

1st rownan
2nd rownan
3rd row<p>Initially a series of behind-the-scenes vlogs, <b>Going Seventeen</b> has taken a more structured route since mid-2019 and is now a reality-variety show with themed episodes. Every week, the members of Seventeen play games or participate in a variety of activities for everyone's delight and entertainment. Season 2021's keyword is "Watch What You Say", meaning that anything the members say can and will be turned into content...</p>
4th row<p>One day in 20XX, the alien pig prince who planned to take a human body as his home arrived on Earth, but unexpectedly discovered that the human being he wanted to live in had not yet been born! The pig prince, who has nowhere to settle down, got to know Saiji and Rubi. The three pulled various funny pranks on humans, causing humans to have baldness, bad breath, headaches, emotional crisis and other problems.</p>
5th row<p>The master of Ye Xing Yun will ascend to heaven, leaving behind the great strength of the Tian Yuan Sect, and Ye Xing Yun making the new Sovereign of the Tian Yuan Sect, and at the request of his master, seek revenge by entering into a small family while waiting to perform revenge. Ye Xing Yun embarks on an extremely dangerous road, but with his strategy, and with the help of the masters of the Tian Yuan Sect, his long-term strategy of confrontation with the huge Zhou dynasty.</p>

Common Values

ValueCountFrequency (%)
nan23
21.1%
<p><b>Hilda</b> follows the adventures of a fearless blue-haired girl as she travels from her home in a vast magical wilderness full of elves and giants, to the bustling city of Trolberg, where she meets new friends and mysterious creatures who are stranger - and more dangerous - than she ever expected.</p>13
 
11.9%
<p><b>Tiny Pretty Things</b> is set in the world of an elite ballet academy and charts the rise and fall of young adults who live far from their homes, each standing on the verge of greatness or ruin. As Chicago's only elite dance school, the Archer School of Ballet serves as the company school for the city's renowned professional company: City Works Ballet. The Archer School is an oasis for an array of dancers: rich and poor, from north and south, and a range of backgrounds. Yet they all share a rare talent and passion for dance, a loyal sense of community... and when it comes to their dreams, no Plan B.</p>10
 
9.2%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>8
 
7.3%
<p>A documentary series about Tofaş owners and culture from 7 regions of Turkey.</p>5
 
4.6%
<p><b>Professionals</b> is set against a backdrop of international espionage and corporate sabotage in the 21st century's privately-funded space race and follows hardened former counterintelligence officer Captain Vincent Corbo. After their advanced medical satellite explodes on deployment, billionaire futurist Peter Swann and his fiancée, medical visionary Dr. Graciela "Grace" Davila, turn to Corbo. Corbo assembles a team of experienced professionals to investigate the incident. They learn that any combination of Swann's business rivals, corrupt governments officials, and a shadowy crime syndicate could be behind the attack and represent a continued threat.</p>2
 
1.8%
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>2
 
1.8%
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>2
 
1.8%
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>2
 
1.8%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
1.8%
Other values (39)40
36.7%

Length

2022-05-09T21:12:22.491805image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the268
 
5.0%
and230
 
4.3%
of199
 
3.7%
a144
 
2.7%
to142
 
2.7%
in89
 
1.7%
their62
 
1.2%
from58
 
1.1%
for54
 
1.0%
as54
 
1.0%
Other values (1348)4028
75.6%

Most occurring characters

ValueCountFrequency (%)
5209
16.6%
e2887
 
9.2%
a2050
 
6.5%
o1864
 
5.9%
t1862
 
5.9%
n1764
 
5.6%
r1650
 
5.3%
s1645
 
5.2%
i1405
 
4.5%
h1215
 
3.9%
Other values (111)9872
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter23818
75.8%
Space Separator5219
 
16.6%
Other Punctuation855
 
2.7%
Uppercase Letter839
 
2.7%
Math Symbol554
 
1.8%
Dash Punctuation71
 
0.2%
Decimal Number56
 
0.2%
Close Punctuation5
 
< 0.1%
Open Punctuation5
 
< 0.1%
Currency Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2887
12.1%
a2050
 
8.6%
o1864
 
7.8%
t1862
 
7.8%
n1764
 
7.4%
r1650
 
6.9%
s1645
 
6.9%
i1405
 
5.9%
h1215
 
5.1%
l1024
 
4.3%
Other values (53)6452
27.1%
Uppercase Letter
ValueCountFrequency (%)
T107
 
12.8%
A77
 
9.2%
S69
 
8.2%
B53
 
6.3%
Y53
 
6.3%
W52
 
6.2%
M39
 
4.6%
C38
 
4.5%
P38
 
4.5%
L32
 
3.8%
Other values (20)281
33.5%
Other Punctuation
ValueCountFrequency (%)
,290
33.9%
.260
30.4%
/140
16.4%
'79
 
9.2%
"40
 
4.7%
:29
 
3.4%
!10
 
1.2%
?5
 
0.6%
&1
 
0.1%
;1
 
0.1%
Decimal Number
ValueCountFrequency (%)
013
23.2%
213
23.2%
18
14.3%
77
12.5%
35
 
8.9%
95
 
8.9%
53
 
5.4%
81
 
1.8%
61
 
1.8%
Space Separator
ValueCountFrequency (%)
5209
99.8%
 10
 
0.2%
Math Symbol
ValueCountFrequency (%)
<277
50.0%
>277
50.0%
Dash Punctuation
ValueCountFrequency (%)
-63
88.7%
8
 
11.3%
Close Punctuation
ValueCountFrequency (%)
)5
100.0%
Open Punctuation
ValueCountFrequency (%)
(5
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin24269
77.2%
Common6766
 
21.5%
Cyrillic388
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2887
11.9%
a2050
 
8.4%
o1864
 
7.7%
t1862
 
7.7%
n1764
 
7.3%
r1650
 
6.8%
s1645
 
6.8%
i1405
 
5.8%
h1215
 
5.0%
l1024
 
4.2%
Other values (49)6903
28.4%
Cyrillic
ValueCountFrequency (%)
е38
 
9.8%
и38
 
9.8%
т37
 
9.5%
о35
 
9.0%
с25
 
6.4%
а24
 
6.2%
н24
 
6.2%
м21
 
5.4%
в16
 
4.1%
р15
 
3.9%
Other values (24)115
29.6%
Common
ValueCountFrequency (%)
5209
77.0%
,290
 
4.3%
<277
 
4.1%
>277
 
4.1%
.260
 
3.8%
/140
 
2.1%
'79
 
1.2%
-63
 
0.9%
"40
 
0.6%
:29
 
0.4%
Other values (18)102
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII31003
98.7%
Cyrillic388
 
1.2%
None24
 
0.1%
Punctuation8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5209
16.8%
e2887
 
9.3%
a2050
 
6.6%
o1864
 
6.0%
t1862
 
6.0%
n1764
 
5.7%
r1650
 
5.3%
s1645
 
5.3%
i1405
 
4.5%
h1215
 
3.9%
Other values (68)9452
30.5%
Cyrillic
ValueCountFrequency (%)
е38
 
9.8%
и38
 
9.8%
т37
 
9.5%
о35
 
9.0%
с25
 
6.4%
а24
 
6.2%
н24
 
6.2%
м21
 
5.4%
в16
 
4.1%
р15
 
3.9%
Other values (24)115
29.6%
None
ValueCountFrequency (%)
 10
41.7%
ş5
20.8%
é4
 
16.7%
ā1
 
4.2%
ç1
 
4.2%
ı1
 
4.2%
è1
 
4.2%
å1
 
4.2%
Punctuation
ValueCountFrequency (%)
8
100.0%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct60
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1634138379
Minimum1602172227
Maximum1652117487
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-05-09T21:12:22.851881image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1602172227
5-th percentile1611477684
Q11618466682
median1639077815
Q31645388626
95-th percentile1651771938
Maximum1652117487
Range49945260
Interquartile range (IQR)26921944

Descriptive statistics

Standard deviation14617492.36
Coefficient of variation (CV)0.008945076226
Kurtosis-1.124807076
Mean1634138379
Median Absolute Deviation (MAD)9112243
Skewness-0.6059062332
Sum1.781210833 × 1011
Variance2.13671083 × 1014
MonotonicityNot monotonic
2022-05-09T21:12:23.241380image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
163907781513
 
11.9%
163766347310
 
9.2%
16124781458
 
7.3%
16115389485
 
4.6%
16151929545
 
4.6%
16430576955
 
4.6%
16196365813
 
2.8%
16481900582
 
1.8%
16090607262
 
1.8%
16508264802
 
1.8%
Other values (50)54
49.5%
ValueCountFrequency (%)
16021722271
 
0.9%
16090607262
 
1.8%
16095351412
 
1.8%
16114368421
 
0.9%
16115389485
4.6%
16124781458
7.3%
16130883481
 
0.9%
16133564461
 
0.9%
16151929545
4.6%
16164229131
 
0.9%
ValueCountFrequency (%)
16521174871
0.9%
16520047082
1.8%
16519332091
0.9%
16518386471
0.9%
16517773161
0.9%
16517638721
0.9%
16515703161
0.9%
16509088001
0.9%
16508264802
1.8%
16505470441
0.9%

_links_self_href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/2176148
 
1
https://api.tvmaze.com/episodes/1996399
 
1
https://api.tvmaze.com/episodes/1955318
 
1
https://api.tvmaze.com/episodes/1996786
 
1
Other values (104)
104 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4251
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.9%
https://api.tvmaze.com/episodes/21761481
 
0.9%
https://api.tvmaze.com/episodes/19963991
 
0.9%
https://api.tvmaze.com/episodes/19553181
 
0.9%
https://api.tvmaze.com/episodes/19967861
 
0.9%
https://api.tvmaze.com/episodes/19493361
 
0.9%
https://api.tvmaze.com/episodes/19493351
 
0.9%
https://api.tvmaze.com/episodes/19493341
 
0.9%
https://api.tvmaze.com/episodes/19493331
 
0.9%
https://api.tvmaze.com/episodes/19493321
 
0.9%
Other values (99)99
90.8%

Length

2022-05-09T21:12:23.554350image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.9%
https://api.tvmaze.com/episodes/20927291
 
0.9%
https://api.tvmaze.com/episodes/19640001
 
0.9%
https://api.tvmaze.com/episodes/19954051
 
0.9%
https://api.tvmaze.com/episodes/20077601
 
0.9%
https://api.tvmaze.com/episodes/19857891
 
0.9%
https://api.tvmaze.com/episodes/20396221
 
0.9%
https://api.tvmaze.com/episodes/20396231
 
0.9%
https://api.tvmaze.com/episodes/23244271
 
0.9%
https://api.tvmaze.com/episodes/23244281
 
0.9%
Other values (99)99
90.8%

Most occurring characters

ValueCountFrequency (%)
/436
 
10.3%
p327
 
7.7%
s327
 
7.7%
e327
 
7.7%
t327
 
7.7%
o218
 
5.1%
a218
 
5.1%
i218
 
5.1%
.218
 
5.1%
m218
 
5.1%
Other values (16)1417
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2725
64.1%
Other Punctuation763
 
17.9%
Decimal Number763
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p327
12.0%
s327
12.0%
e327
12.0%
t327
12.0%
o218
8.0%
a218
8.0%
i218
8.0%
m218
8.0%
h109
 
4.0%
d109
 
4.0%
Other values (3)327
12.0%
Decimal Number
ValueCountFrequency (%)
9119
15.6%
2114
14.9%
199
13.0%
097
12.7%
366
8.7%
663
8.3%
860
7.9%
753
6.9%
449
6.4%
543
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/436
57.1%
.218
28.6%
:109
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2725
64.1%
Common1526
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/436
28.6%
.218
14.3%
9119
 
7.8%
2114
 
7.5%
:109
 
7.1%
199
 
6.5%
097
 
6.4%
366
 
4.3%
663
 
4.1%
860
 
3.9%
Other values (3)145
 
9.5%
Latin
ValueCountFrequency (%)
p327
12.0%
s327
12.0%
e327
12.0%
t327
12.0%
o218
8.0%
a218
8.0%
i218
8.0%
m218
8.0%
h109
 
4.0%
d109
 
4.0%
Other values (3)327
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/436
 
10.3%
p327
 
7.7%
s327
 
7.7%
e327
 
7.7%
t327
 
7.7%
o218
 
5.1%
a218
 
5.1%
i218
 
5.1%
.218
 
5.1%
m218
 
5.1%
Other values (16)1417
33.3%

Interactions

2022-05-09T21:12:00.737628image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:08.083485image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:20.070670image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:24.176419image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:29.558003image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:35.140316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:41.679668image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:46.033634image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:55.051737image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:03.649784image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:11.684869image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:21.925557image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:26.016018image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:32.709258image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:36.776819image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:43.170384image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:50.097455image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:57.526497image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:03.901283image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:12.873577image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:22.060019image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:26.202765image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:32.883196image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:37.265817image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:43.397544image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:50.506431image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:57.728452image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:04.101535image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:13.713610image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:22.227718image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:26.469445image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:33.082744image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:37.696429image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:43.577209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:50.945562image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:57.982405image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:04.340160image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:14.735252image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:22.416577image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:26.809510image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:33.341000image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:38.105800image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:43.871592image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:51.479365image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:58.190661image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:05.670048image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:16.394177image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:23.354476image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:28.594819image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:34.294824image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:39.290109image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:44.858531image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:53.656536image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:59.605333image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:06.056919image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:17.352920image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:23.517304image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:28.796817image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:34.470765image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:39.596124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:45.161236image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:54.042908image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:59.849441image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:06.277197image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:18.346157image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:23.676240image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:29.015202image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:34.776389image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:40.218776image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:45.493256image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:54.345088image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:00.154194image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:06.486025image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:19.232536image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:23.824129image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:29.240869image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:34.950137image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:40.943707image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:45.749604image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:11:54.799499image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:12:00.425680image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:12:23.777304image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:12:24.392517image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:12:24.792855image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:12:25.269611image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:12:25.910101image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:12:06.958362image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:12:09.230315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:12:09.787180image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:12:10.090182image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
01982403https://www.tvmaze.com/episodes/1982403/volk-1x05-seria-05Серия 051.05.0regular2020-12-14nan2020-12-14T00:00:00+00:0048.0Nonenan52181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian['Drama', 'Adventure', 'Mystery']Ended51.050.02020-12-072020-12-28https://premier.one/show/1233925.0nannan1.640436e+09https://api.tvmaze.com/episodes/1977902
11982404https://www.tvmaze.com/episodes/1982404/volk-1x06-seria-06Серия 061.06.0regular2020-12-14nan2020-12-14T00:00:00+00:0051.0Nonenan52181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian['Drama', 'Adventure', 'Mystery']Ended51.050.02020-12-072020-12-28https://premier.one/show/1233925.0nannan1.640436e+09https://api.tvmaze.com/episodes/2015818
22140387https://www.tvmaze.com/episodes/2140387/going-seventeen-2020-12-14-going-vs-seventeen-1GOING VS SEVENTEEN #12020.042.0regular2020-12-14nan2020-12-14T03:00:00+00:0030.0Nonenan56655https://www.tvmaze.com/shows/56655/going-seventeenGoing SeventeenVarietyKorean[]Running30.030.02017-06-12nannan18.0nan<p>Initially a series of behind-the-scenes vlogs, <b>Going Seventeen</b> has taken a more structured route since mid-2019 and is now a reality-variety show with themed episodes. Every week, the members of Seventeen play games or participate in a variety of activities for everyone's delight and entertainment. Season 2021's keyword is "Watch What You Say", meaning that anything the members say can and will be turned into content...</p>1.651764e+09https://api.tvmaze.com/episodes/1964000
31945592https://www.tvmaze.com/episodes/1945592/my-little-invisible-being-1x12-episode-12Episode 121.012.0regular2020-12-1412:002020-12-14T04:00:00+00:005.0Nonenan50916https://www.tvmaze.com/shows/50916/my-little-invisible-beingMy Little Invisible BeingAnimationChinese['Comedy', 'Anime']Running5.05.02020-10-05nanhttps://www.bilibili.com/bangumi/media/md28229943/3.0nan<p>One day in 20XX, the alien pig prince who planned to take a human body as his home arrived on Earth, but unexpectedly discovered that the human being he wanted to live in had not yet been born! The pig prince, who has nowhere to settle down, got to know Saiji and Rubi. The three pulled various funny pranks on humans, causing humans to have baldness, bad breath, headaches, emotional crisis and other problems.</p>1.602172e+09https://api.tvmaze.com/episodes/1995405
42065442https://www.tvmaze.com/episodes/2065442/the-wonderland-of-ten-thousands-4x29-episode-29-157Episode 29 (157)4.029.0regular2020-12-14nan2020-12-14T04:00:00+00:0010.0Nonenan54610https://www.tvmaze.com/shows/54610/the-wonderland-of-ten-thousandsThe Wonderland of Ten ThousandsAnimationChinese['Anime', 'Fantasy', 'Romance']Running10.010.02018-03-30nanhttps://v.qq.com/detail/5/5cuf8ahvxvm2587.html65.0nan<p>The master of Ye Xing Yun will ascend to heaven, leaving behind the great strength of the Tian Yuan Sect, and Ye Xing Yun making the new Sovereign of the Tian Yuan Sect, and at the request of his master, seek revenge by entering into a small family while waiting to perform revenge. Ye Xing Yun embarks on an extremely dangerous road, but with his strategy, and with the help of the masters of the Tian Yuan Sect, his long-term strategy of confrontation with the huge Zhou dynasty.</p>1.646256e+09https://api.tvmaze.com/episodes/2007760
52071477https://www.tvmaze.com/episodes/2071477/youths-in-the-breeze-1x07-the-boy-and-the-cat-07THE BOY AND THE CAT #071.07.0regular2020-12-14nan2020-12-14T04:00:00+00:007.0Nonenan54762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese['Drama', 'Fantasy']Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef28.0nan<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1.618467e+09https://api.tvmaze.com/episodes/1985789
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